Metadata-Version: 2.4
Name: gnn-exp
Version: 0.1.0
Summary: Visual exploration and explanation of Graph Neural Networks in computational notebooks
Author-email: Yilin Lu <lu000661@umn.edu>, Qianwen Wang <qianwen@umn.edu>
License: MIT
Project-URL: Homepage, https://github.com/HarryLuUMN/gnn-vis-widgets
Project-URL: Repository, https://github.com/HarryLuUMN/gnn-vis-widgets
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: anywidget>=0.9.0
Dynamic: license-file

# gnn-exp: Visual Exploration and Explanation of Graph Neural Networks in Your Computational Notebook

The repository contains a graph neural network visualization library adopted from our previous work GNN101. 

## Installation

```sh
pip install gnn_vis_widgets
```

or with [uv](https://github.com/astral-sh/uv):

```sh
uv add gnn_vis_widgets
```

## Development

We recommend using [uv](https://github.com/astral-sh/uv) for development.
It will automatically manage virtual environments and dependencies for you.

```sh
uv run jupyter lab example.ipynb
```

Alternatively, create and manage your own virtual environment:

```sh
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
jupyter lab example.ipynb
```

The widget front-end code bundles it's JavaScript dependencies. After setting up Python,
make sure to install these dependencies locally:

```sh
npm install
```

While developing, you can run the following in a separate terminal to automatically
rebuild JavaScript as you make changes:

```sh
npm run dev
```

Open `example.ipynb` in JupyterLab, VS Code, or your favorite editor
to start developing. Changes made in `js/` will be reflected
in the notebook.
